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首页> 外文期刊>Physical review, C >Calculation of nuclear charge radii with a trained feed-forward neural network
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Calculation of nuclear charge radii with a trained feed-forward neural network

机译：用训练前进神经网络计算核电半径

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A feed-forward neural network model is trained to calculate the nuclear charge radii. The model is trained with the input data set of proton and neutron number Z, N, the electric quadrupole transition strength B(E2) from the first excited 2(+) state to the ground state, together with the symmetry energy. The model reproduces well not only the isotope dependence of charge radii, but also the kinks of charge radii at the neutron magic numbers N = 82 for Sn and Sm isotopes, and also N = 126 for Pb isotopes. The important role of the B(E2) value is pointed out to reproduce the kink of the isotope dependence of charge radii in these nuclei. Moreover, with the inclusion of the symmetry energy term in the inputs, the charge radii of Ca isotopes are well reproduced. This result suggests a new correlation between the symmetry energy and charge radii of Ca isotopes. The Skyrme Hartree-Fock-Bogoliubov calculation is performed to confirm the existence of this correlation in a microscopic model.
机译：训练前馈神经网络模型计算核电荷半径。该模型由质子和中子数Z，N，从第一激发态到基态的电四极跃迁强度B（E2）以及对称能量的输入数据集训练而成。该模型不仅很好地再现了电荷半径的同位素依赖性，而且很好地再现了Sn和Sm同位素在中子幻数N=82时的电荷半径扭结，以及Pb同位素在中子幻数N=126时的电荷半径扭结。指出了B（E2）值在再现这些核中电荷半径的同位素依赖性扭结方面的重要作用。此外，在输入中加入了对称能量项，可以很好地再现钙同位素的电荷半径。这一结果表明，钙同位素的对称能量和电荷半径之间存在一种新的相关性。进行Skyrme-Hartree-Fock-Bogoliubov计算，以确认微观模型中存在这种相关性。

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